{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PyTorch 模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn.functional as F\n",
    "from torch import fx\n",
    "from torch.nn import Module\n",
    "from torchvision.models.resnet import ResNet18_Weights, resnet18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tvm.relax.frontend.torch import from_fx\n",
    "import tvm\n",
    "from tvm import relax\n",
    "from tvm.script import ir as I\n",
    "from tvm.script import relax as R\n",
    "from tvm.script import tir as T\n",
    "from tvm.relax.frontend import detach_params\n",
    "\n",
    "def verify_model(torch_model, input_info, binding, expected):\n",
    "    graph_model = fx.symbolic_trace(torch_model)\n",
    "    with torch.no_grad():\n",
    "        mod = from_fx(graph_model, input_info)\n",
    "    binding = {k: tvm.nd.array(v) for k, v in binding.items()}\n",
    "    expected = relax.transform.BindParams(\"main\", binding)(expected)\n",
    "    tvm.ir.assert_structural_equal(mod, expected)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch_model = resnet18(weights=ResNet18_Weights.DEFAULT)\n",
    "input_info = [([1, 3, 224, 224], \"float32\")]\n",
    "graph_model = fx.symbolic_trace(torch_model)\n",
    "with torch.no_grad():\n",
    "    mod = from_fx(graph_model, input_info)\n",
    "    mod = relax.transform.FoldConstant()(mod)\n",
    "    # mod = relax.transform.FuseOps()(mod)\n",
    "    # mod = relax.get_pipeline(\"zero\")(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"highlight\" style=\"background: \"><pre style=\"line-height: 125%;\"><span></span><span style=\"color: #007979; font-style: italic\"># from tvm.script import ir as I</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import relax as R</span>\n",
       "\n",
       "<span style=\"color: #AA22FF\">@I</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>ir_module\n",
       "<span style=\"color: #008000; font-weight: bold\">class</span> <span style=\"color: #0000FF; font-weight: bold\">Module</span>:\n",
       "    <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">main</span>(inp_0: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">224</span>, <span style=\"color: #008000\">224</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1000</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>):\n",
       "        <span style=\"color: #008000; font-weight: bold\">with</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>dataflow():\n",
       "            lv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">112</span>, <span style=\"color: #008000\">112</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(inp_0, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">0</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">112</span>, <span style=\"color: #008000\">112</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">1</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">2</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">3</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">4</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">112</span>, <span style=\"color: #008000\">112</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv1[<span style=\"color: #008000\">0</span>]\n",
       "            lv3: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">112</span>, <span style=\"color: #008000\">112</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv2)\n",
       "            lv4: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>max_pool2d(lv3, pool_size<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">3</span>, <span style=\"color: #008000\">3</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], ceil_mode<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">False</span>, count_include_pad<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">False</span>, layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>)\n",
       "            lv5: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv4, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">5</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv6: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv5, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">6</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">7</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">8</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">9</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv7: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv6[<span style=\"color: #008000\">0</span>]\n",
       "            lv8: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv7)\n",
       "            lv9: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv8, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">10</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv10: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv9, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">11</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">12</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">13</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">14</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv11: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv10[<span style=\"color: #008000\">0</span>]\n",
       "            lv12: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv11, lv4)\n",
       "            lv13: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv12)\n",
       "            lv14: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv13, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">15</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv15: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv14, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">16</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">17</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">18</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">19</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv16: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv15[<span style=\"color: #008000\">0</span>]\n",
       "            lv17: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv16)\n",
       "            lv18: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv17, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">20</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv19: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv18, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">21</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">22</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">23</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">24</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv20: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv19[<span style=\"color: #008000\">0</span>]\n",
       "            lv21: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv20, lv13)\n",
       "            lv22: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">56</span>, <span style=\"color: #008000\">56</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv21)\n",
       "            lv23: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv22, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">25</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv24: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv23, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">26</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">27</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">28</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">29</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv25: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv24[<span style=\"color: #008000\">0</span>]\n",
       "            lv26: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv25)\n",
       "            lv27: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv26, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">30</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv28: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv27, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">31</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">32</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">33</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">34</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv29: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv28[<span style=\"color: #008000\">0</span>]\n",
       "            lv30: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv22, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">35</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv31: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv30, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">36</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">37</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">38</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">39</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv32: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv31[<span style=\"color: #008000\">0</span>]\n",
       "            lv33: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv29, lv32)\n",
       "            lv34: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv33)\n",
       "            lv35: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv34, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">40</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv36: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv35, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">41</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">42</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">43</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">44</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv37: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv36[<span style=\"color: #008000\">0</span>]\n",
       "            lv38: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv37)\n",
       "            lv39: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv38, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">45</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv40: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">128</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv39, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">46</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">47</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">48</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">49</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv41: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv40[<span style=\"color: #008000\">0</span>]\n",
       "            lv42: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv41, lv34)\n",
       "            lv43: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">128</span>, <span style=\"color: #008000\">28</span>, <span style=\"color: #008000\">28</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv42)\n",
       "            lv44: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv43, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">50</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv45: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv44, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">51</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">52</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">53</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">54</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv46: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv45[<span style=\"color: #008000\">0</span>]\n",
       "            lv47: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv46)\n",
       "            lv48: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv47, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">55</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv49: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv48, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">56</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">57</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">58</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">59</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv50: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv49[<span style=\"color: #008000\">0</span>]\n",
       "            lv51: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv43, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">60</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv52: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv51, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">61</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">62</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">63</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">64</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv53: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv52[<span style=\"color: #008000\">0</span>]\n",
       "            lv54: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv50, lv53)\n",
       "            lv55: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv54)\n",
       "            lv56: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv55, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">65</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv57: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv56, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">66</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">67</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">68</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">69</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv58: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv57[<span style=\"color: #008000\">0</span>]\n",
       "            lv59: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv58)\n",
       "            lv60: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv59, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">70</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv61: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">256</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv60, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">71</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">72</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">73</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">74</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv62: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv61[<span style=\"color: #008000\">0</span>]\n",
       "            lv63: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv62, lv55)\n",
       "            lv64: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">256</span>, <span style=\"color: #008000\">14</span>, <span style=\"color: #008000\">14</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv63)\n",
       "            lv65: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv64, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">75</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv66: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv65, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">76</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">77</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">78</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">79</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv67: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv66[<span style=\"color: #008000\">0</span>]\n",
       "            lv68: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv67)\n",
       "            lv69: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv68, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">80</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv70: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv69, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">81</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">82</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">83</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">84</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv71: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv70[<span style=\"color: #008000\">0</span>]\n",
       "            lv72: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv64, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">85</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">2</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv73: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv72, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">86</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">87</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">88</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">89</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv74: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv73[<span style=\"color: #008000\">0</span>]\n",
       "            lv75: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv71, lv74)\n",
       "            lv76: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv75)\n",
       "            lv77: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv76, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">90</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv78: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv77, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">91</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">92</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">93</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">94</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv79: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv78[<span style=\"color: #008000\">0</span>]\n",
       "            lv80: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv79)\n",
       "            lv81: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv80, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">95</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv82: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">512</span>,), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>batch_norm(lv81, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">96</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">97</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">98</span>], metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">99</span>], axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, epsilon<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1.0000000000000001e-05</span>, center<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, scale<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>, momentum<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">0.10000000000000001</span>)\n",
       "            lv83: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv82[<span style=\"color: #008000\">0</span>]\n",
       "            lv84: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv83, lv76)\n",
       "            lv85: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">7</span>, <span style=\"color: #008000\">7</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv84)\n",
       "            lv86: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>adaptive_avg_pool2d(lv85, output_size<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>)\n",
       "            lv87: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv86, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">512</span>]))\n",
       "            lv89: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1000</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>matmul(lv87, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">100</span>], out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)\n",
       "            lv90: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1000</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv89, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">101</span>])\n",
       "            gv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1000</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv90\n",
       "            R<span style=\"color: #AA22FF; font-weight: bold\">.</span>output(gv)\n",
       "        <span style=\"color: #008000; font-weight: bold\">return</span> gv\n",
       "\n",
       "<span style=\"color: #007979; font-style: italic\"># Metadata omitted. Use show_meta=True in script() method to show it.</span>\n",
       "</pre></div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mod.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "target = tvm.target.Target(\"llvm\")\n",
    "ex = relax.build(mod, target)\n",
    "device = tvm.cpu()\n",
    "vm = relax.VirtualMachine(ex, device)\n",
    "data = np.random.rand(1, 3, 224, 224).astype(\"float32\")\n",
    "tvm_data = tvm.nd.array(data, device=device)\n",
    "tvm_output = vm[\"main\"](tvm_data).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with torch.no_grad():\n",
    "    torch_output = graph_model(torch.from_numpy(data)).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.testing.assert_allclose(tvm_output, torch_output, rtol=1e-07, atol=1e-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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